The Palettable API has also been updated for the IPython age. All available palettes are now loaded at import and are available for your tab-completion pleasure. Need the YlGnBu palette with nine colors? That’s now available at palettable.colorbrewer.sequential.YlGnBu_9. Reversed palettes are also available with a _r suffix.

A friend recently tweeted: “Who knows of a python code that intelligently picks colors based on the number needed for a plot?” Phil is plotting several datasets on one plot and wanted an easy way to get a good set of colors to use. I mentioned colorbrewer2.org, which has terrific color maps, but they are locked up in a Flash application. So I had the idea to make a Python package bringing the colorbrewer2.org color maps into Python and connecting them to matplotlib.

There is an existing Python package called colorbrewer but it’s undocumented, doesn’t have its code in a public repository, and is missing some features I wanted. (And it was updated for the first time in 3 years on the day I wrote this post.) It also turns out that the colorbrewer2.org color maps are already in matplotlib (all the capitalized maps in this example) but that doesn’t give access the original colors as defined by colorbrewer2.org. And so was born brewer2mpl.

colorbrewer2.org has three types of color maps: sequential, diverging, and qualitative (for categorical data). Each color map is defined several times with different numbers of colors, anywhere from three to 12.

brewer2mpl packages the colorbrewer2.org color maps and gives access to them as 0-255 RGB triplets, 0-1 RGB triplets, hex strings, and matplotlib color maps. It contains functions for listing color maps by type and number of defined colors. Now Phil can do the following to get some good colors to use in matplotlib plots:

This was my first time building and releasing my own package. It was fun and a great chance to learn about the simplest aspects of releasing Python packages. (Nothing fancy going on here.) Hope I get the chance to do more!